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Conference papers

Slope heuristics for multiple change-point models

Yann Guédon 1, 2, *
* Corresponding author
2 VIRTUAL PLANTS - Modeling plant morphogenesis at different scales, from genes to phenotype
CRISAM - Inria Sophia Antipolis - Méditerranée , INRA - Institut National de la Recherche Agronomique, UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales
Abstract : With regard to multiple change-point models, much effort has been devoted to the selection of the number of change points. But, the proposed approaches are either dedicated to specific segment models or give unsatisfactory results for short or medium length sequences. We propose to apply the slope heuristic, a recently proposed non-asymptotic penalized likelihood criterion, for selecting the number of change points. In particular we apply the data-driven slope estimation method, the key point being to define a relevant penalty shape. The proposed approach is illustrated using two benchmark data sets.
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Submitted on : Tuesday, December 8, 2015 - 3:47:19 PM
Last modification on : Thursday, March 24, 2022 - 3:37:15 AM
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  • HAL Id : hal-01240037, version 1


Yann Guédon. Slope heuristics for multiple change-point models. 30th International Workshop on Statistical Modelling (IWSM 2015), Statistical Modelling Society, Jul 2015, Linz, Austria. ⟨hal-01240037⟩



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